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Modest XML for corpora: not a standard, but a suggestion

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>04/2014
<mark>Journal</mark>ICAME Journal
Issue number1
Volume38
Number of pages31
Pages (from-to)73-103
Publication StatusPublished
<mark>Original language</mark>English

Abstract

This paper argues for, and presents, a modest approach to XML encoding for use by the majority of contemporary linguists who need to engage in corpus construction. While extensive standards for corpus encoding exist - most notably, the Text Encoding Initiative’s Guidelines and the Corpus Encoding Standard based on them - these are rather heavyweight approaches, implicitly intended for major corpus-building projects, which are rather different from the increasingly common efforts in corpus construction undertaken by individual researchers in support of their personal research goals. Therefore, there is a clear benefit to be had from a set of recommendations (not a standard) that outlines general best practices in the use of XML in corpora without going into any of the more technical aspects of XML or the full weight of TEI encoding. This paper presents such a set of suggestions, dubbed Modest XML for Corpora, and posits that such a set of pointers to a limited level of XML knowledge could work as part of the normal, general training of corpus linguists.

The Modest XML recommendations cover the following set of things, which, according to the foregoing argument, are sufficient knowledge about XML for most corpus linguists’ day-to-day needs: use of tags; adding attribute value pairs; recommended use of attributes; nesting of tags; encoding of special characters; XML well-formedness; a collection of de facto standard tags and attributes; going beyond the basic de facto standard tags; and text headers.

Bibliographic note

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY-NC-ND 3.0)